| itle: “Tidytuesday Screencast” |
| ubtitle: “how a data scientist approaches data analysis” |
| uthor: “Adam Nelson” |
| utput: |
| html_document: |
| toc: true |
Choose one of David Robinson’s tidytuesday screencasts, watch the video, and summarise. https://www.youtube.com/channel/UCeiiqmVK07qhY-wvg3IZiZQ
The riddler
December 12, 2018
Hint: What’s the source of the data; what does the row represent; how many observations?; what are the variables; and what do they mean?
He is pulling the data from a webiste that has riddles, this specific riddle is trying to indicate if a man wlaing to work will get wet on his way from rain. He lays out a trial period of 500 days. Th variables are if it will or will not rain as well as the percentage of chance wich is 50% in the moring and 40% in the evening. ## Q4-Q5 Describe how Dave approached the analysis each step. Hint: For example, importing data, understanding the data, data exploration, etc. He kept reassening how the data was being shown,and also chaninging what the variable were like moring to morning comute, aswell as chnaging the ifnromation was orginized making sure moringing came before evening.
Ive seen a few hings that we learned in class. We were taught the use f tidyverse and how to insert the cide. Aswell as the use of the global coding and using things like true or false make thing shown and nit shown.
The major finding was the you luie was way less likely to get wet and not have an umbrella on friday morning, and way more likley to get wet and not have and umbreeella on firday evening.
I liked how clear and concise he made the data.The overall data was very easy to read and undertsand. There wasnt any serious complexcity to it.